Eddy Analysis in the Subtropical Zonal Band of the North Pacific Ocean

Transcription

1 1 2 Eddy Analysis in the Subtropical Zonal Band of the North Pacific Ocean Yu Liu 1,2, Changming Dong 3, Yu Ping Guan 1, Dake Chen 4, James McWilliams Key Laboratory of Tropical Marine Environmental Dynamic (LED), South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, , China 2 Graduate University of the Chinese Academy of Sciences, Beijing, , China 3 Institute of Geophysics and Planetary Physics University of California, Los Angeles, CA 90095, USA 4 State Key Laboratory of Satellite Oceanic Environment and Dynamics, SIO/SOA, Hangzhou, , China 15 Submitted to JGR-Ocean 1 Corresponding author address: Dr. Yu Ping Guan, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou , China. guan@scsio.ac.cn 1

2 16 ABSTRACT There are two zonal bands of eminently high eddy kinetic energy (EKE) in the North Pacific Ocean. The highest one is located in the Kuroshio Extension and the second one is in the subtropical area. This paper is focused on the latter. The following observational data are used: satellite measured sea surface height anomalies (SSHA), sea surface temperature (SST), Argo data and QuikSCAT wind. An eddy detection scheme based on velocity geometry is applied to the SSHA-derived geostrophic currents to identify and track eddies, and generate an eddy dataset in the band, including spatial and temporal information of eddy generation, evolution and termination. Through the analysis of the eddy data set, a series of eddy characteristic parameters are investigated. The eddy location and time information is used to track observed Argo vertical profiles falling in eddy areas, which exposes how eddies impact the thermocline and halocline. The frontal intensity derived from the SST data and wind curls estimated from QuikSCAT wind data are used to explain the mechanism of temporal and spatial eddy variations in the zonal band. 2

3 Introduction Mesoscale eddy activity is an outstanding phenomenon in the upper ocean. However, oceanic eddy generation is not spatially uniform, and concentrated in certain special regions. In the Northern Pacific Ocean, particularly, there are two zonal bands of strong eddy activities [Aoki and Imawaki, 1996; Wunsch and Stammer, 1998; Qiu, 1999; Qiu and Chen, 2010]. The spatial distribution of eddy kinetic energy calculated from altimetry-measured sea surface height anomalies (SSHA) with respect to the long-term mean and after high-pass filtering (shorter than 90 days and longer than 7 days) is shown in Fig. 1. These two high EKE zonal bands can be easily identified. The bands are also clearly emerged in high-pass root-mean-square sea surface height anomalies, e.g., Qiu and Chen [2010]. The northern band is collocated with the Kuroshio Extension, and this high EKE band is closely linked to the instability of the Kuroshio after the jet leaves the coastal restraint area and flows to the open ocean, see Qiu and Chen [2010] for a summary. The southern band is located in the subtropical area, extending from east of Luzon Strait all the way to the Hawaii Islands, and this zonal band is the focus of this study In most previous studies on eddy activities the southern band is further divided into two areas along about 170ºE: the western zone, west of 170 E, is the subtropical countercurrent zone [Qiu, 1999; Hwang et al., 2004; Liu et al., 2005; Qiu and Chen, 2010; Kang et al., 2010]; the eastern zone, east of 170 E, is the lee side of Hawaii Islands [e.g., Yu et al., 2003; Dong et al., 2009; Yoshida et al., 2010]. There is one exception, Kobashi and Kawamura [2002], studied eddy variations in the entire southern band. It can be easily 3

4 understood that such separation is based on distinctively different mechanisms of eddy generation: in the former area eddies are generated through frontal instability associated with the subtropical front and in the latter area they are due to wind curl in the wakes of wind and oceanic current past the Hawaii islands. However, a significant number of eddies generated in the eastern zone propagate westward and enter the western zone (see Section 3); moreover, wind curl also works as an important driving force generating eddies in western zone (Sec. 5). Therefore, in this study we examine eddy properties in the entire band as a whole On the other hand, previous studies shown that eddies in the zonal band have impacts on the subtropical gyre [Qiu, 1999], North Pacific Subtropical Mode Water [Uehara et al., 2003; Qiu et al., 2007], North Pacific intermediate water [Qiu and Chen, 2011], subtropical ventilation [Endoh et al., 2006; Nishikawa et al., 2010], vertical mixing [Pan and Liu, 2005], and even biological processes [Vaillancourt et al., 2003; Johnson et al., 2010]. Several approaches have been used to study the eddy variability in this zonal band. Qiu [1999] and Qiu and Chen [2010] used SSHA anomalies to examine eddy variability on the interannual and seasonal time scales. Noh et al. [2007] and Tsujino et al. [2010] applied numerical models to investigate eddy variability. Kang et al. [2010] generated an eddy dataset through identifying eddies from SSHA data, and provided preliminary statistical results. Two global eddy data mappings and analysis by Chelton et al [2007, 2011] include eddy activity information in the area. However, more comprehensive analysis is required for better understanding of characteristic features of eddies and their variability in this band. 4

5 The present study is focused on the area of [15 N-28 N] x [112 E-140 W], see Fig. 1; the data used in this study consists of the following observational data: SSHA, SST, Argo and QuikSCAT wind data. An eddy detection scheme based on velocity geometry is applied to SSHA-derived geostrophic current anomalies to detect and track eddies, and then an eddy dataset is set up. A series of statistical analysis is applied to the eddy dataset to explore features of eddy dynamics. In addition, all vertical profiles from Argo data in the study area from are collected. Information of location and time of eddies detected from the eddy dataset is used as indices to identify Argo vertical profiles falling within these eddies, and these profiles are used to examine the eddy effect on the thermocline and halocline. The rest of the paper is organized as follows: the data and eddy detection scheme used are described in Section 2; statistical analysis of the eddy dataset is presented in Section 3; the application of Argo profiles to study eddy effects on the thermocline and halocline is discussed in Section 4; Section 5 discusses eddy generation mechanisms. Finally, the summary is presented in Section Data and Eddy detection Scheme 2.1 Data The following observational data are used in the present paper: satellite measured sea surface height anomalies (SSHA), Argo float-measured temperature (T) and salinity (S) vertical profiles, sea surface temperature (SST) and QuikSCAT wind vectors. Surface geostrophic velocity anomalies are derived from SSHA data using the 5

6 97 following formula: and, where and are the zonal 98 and meridional components of the geostrophic velocity anomalies, and is the sea level anomaly (SLA) ; is gravitational acceleration and is Coriolis parameter. The data used in this study are taken from AVISO multiple satellite-merged SSHA with a spatial resolution of 1/3 x1/3 and 7-day temporally sampling over the period from January 1993 to December 2009, downloaded from The derived geostrophic velocities are used for eddy detection and eddy characteristic parameter estimation, including eddy location, size, intensity, path and temporal evolution. Argo float T/S vertical profiles are downloaded from ftp:// There are totally over 42,000 floats in the area of study. The data are sampled daily and the maximum depth reachable by Argo floats is about 2000 meters. Spatial (center location and eddy radius) and temporal information from detected eddies are used as indices to identify Argo vertical profiles falling inside these eddies, and these profiles are used to examine eddy impacts on the thermocline and halocline. The Advance Very High Resolution Radiometer (AVHRR) SST data downloaded from ftp://podaac.jpl.nasa.gov/ghrsst/data/l4/glob/ncdc/avhrr_oi/ are used to examine the subtropical front. The data have a horizontal resolution of 25 km. The monthly QuikSCAT wind data are used to explore possible relationship between wind curl and surface vorticity derived from the satellite measured SSHA data. The wind data have a horizontal resolution of 0.5 degree. They are downloaded from 6

7 Eddy Detection Scheme Several schemes of eddy detection have been developed in literature; see Nencioli et al. [2010] for a review. In this paper, an eddy detection scheme based on velocity geometry [Nencioli et al., 2010] is used. For an observer moving with the mean velocity, an eddy can be defined as a flow feature where the relative velocity vectors rotate around a center. The velocity fields associated with mesoscale cyclones and anticyclones are characterized by following common features: a velocity minimum in proximity of their centers, tangential velocities increasing linearly proportional to the distance from the center and deceasing after reaching a maximum value. Furthermore, because of the rotational nature of the motion, the (u,v) components of velocity reverses in sign cross the center of the eddy. In this scheme, four constraints were derived in conformance with the general characteristics associated with the eddy s velocity field and eddy centers at those grid points where all the constraints are satisfied. In addition, an eddy tracking scheme is also included. For more details about the eddy detection scheme the reader is referred to Nencioli et al. [2010] Eddy Analysis In the subtropical zonal band, the EKE estimated from the SSHA-derived geostrophic currents varies on seasonal and interannual time scales, see Fig. 2. The EKE in later spring and early summer (May and June) is much higher than that in other seasons. The level of EKE in and is much lower than normal. Anomalies of both the sea surface EKE and vorticity propagate westward with a speed of 7

8 about 10 cm/s, see Fig. 3. These results are similar to those obtained by Qiu and Chen [2010], whose study is focused on a smaller domain west of 165 W. A primary contribution to the EKE variability is from nonlinear eddies, which can transport both energy and mass [e.g., Chelton et al., 2007]. To better understand activities of these nonlinear eddies, we apply the eddy detection scheme introduced in Sect. 2.2 to seventeen years ( ) SSHA-derived geostrophic current anomalies. Fig. 4 shows an example of detected eddies on April 28, 2008 (only eddies with radius larger than 50 km are displayed). With the eddy detection scheme introduced in Sect 2.2 applied to the above velocity anomaly data, an eddy dataset is generated, and it consists of the following characteristic parameters: eddy size (radius) and boundary, eddy center location (longitude and latitude), eddy polarity, eddy vorticity (averaged over each eddy), eddy kinetic energy (averaged over each eddy) Eddy Number, Size and Lifetime The total number of eddy detected is , including cyclonic eddies and anticyclonic eddies. However, this total number of eddy includes counting repetition of same eddies at different times. If we count each eddy for its whole life time as a single item, the total number of individual eddy detected is 17756: including 9070 cyclonic eddies and 8686 anticyclonic eddies. The total number of cyclonic eddies is about 3% larger than that of anticyclonic eddies. Taking in consideration of possible errors associated with processing SSHA data, in the following analysis we consider eddies with signals lasting longer than or equal to four weeks only. Subject to this 8

9 criterion, there are 4883 cyclonic eddies and 4542 anticyclonic eddies detected in the zonal band. In terms of eddy size, eddy number distribution is a near-gaussian distribution with peak at 50km for the both cyclonic and anticyclonic eddies, and this is approximately the same as the mean first baroclinic radius of deformation of the zonal band of the ocean, as shown in the upper panel of Fig. 5, where a symmetric shape of the histograms is clearly visible. The histogram of the lifetime of eddies, which longer than 4 weeks, is shown in the lower panel of Fig. 5. The numbers of both anticyclonic and cyclonic eddies are approximately symmetric in terms of the lifetime distribution. It is to note that some eddies can survive more than one year. Fig. 6 shows the eddy size distribution, and eddy size is defined as the average for all eddies whose center falls in each 1 x1 bin. Fig. 6 shows the eddy size is maximal at the central latitude and decrease northward and southward. It might be explained with the evolution of eddy radius in Sect. 3.4, where eddies at mature stages always have their largest eddy size during their life time Eddy Vorticity Relative vorticity within an eddy varies from its center (the magnitude of the relative vorticity is maximum at the center theoretically) to its boundary (reaches zero). We define the vorticity of an eddy as the maximum vorticity value within the eddy area confined by its boundary. The spatial distribution of vorticity of detected eddies normalized by the background planetary vorticity, i.e., the Coriolis coefficient, at eddy centers in each 1 x1 bin is plotted in Fig. 7. A high vorticity band can be clearly seen in an area centered with the largest values appearing near the Kuroshio region and the lee 9

10 side of Hawaii Islands. An outstanding phenomenon can be identified from Fig. 7: the eddy normalized vorticity increase westward, except at the vicinity of the wakes of the Hawaii Islands. This implies two potential factors: eddies become stronger on their way westward, and eddies generated in the western part of the latitudinal band are stronger than those generated in the eastern part of the latitudinal band. Further to display the varying trend, the meridional averaged normalized eddy vorticity as a function of the longitude is plotted on the bottom panel of Fig. 7, which shows clearly two peaks near Kuroshio and in the lee of Haiwaii and the westward increase in vorticity magnitude. The histogram of eddy vorticity with eddy lifetimes equal to or longer than 4 weeks is shown in Fig. 8; the symmetrical distribution of vorticity intensity against the eddy size for both positive (cyclonic) and negative (anticyclonic) eddies vorticity can be clearly seen. The peaks of normalized vorticity are near 0.2, i.e. the most popular eddies are with a rather weak relative vorticity, on the order of 20% of the mean planetary vorticity. Another noticeable difference between the cyclonic and anticyclonic eddies is the following: the normalized vorticity for the anticyclonic eddies has a slightly higher peak and slightly narrower band of distribution compared with the cyclonic eddies, i.e. the anticyclonic eddies are slightly stronger or more nonlinear than the cyclonic eddies Eddy Generation and Termination The information about where and when most eddies are generated and terminated can help us identify mechanisms for eddy generation and termination. We define the first (last) record in the time series of each eddy lifetime as the eddy generation (termination); 10

11 however, for a specified region, some eddies can move into (out of) the area, so that they are not generated (terminated) locally. To exclude those eddies, we remove the first (last) 209 records are found within 0.5 strips along four boundaries from the generation (termination) records. The eddy generation number variations with latitude and longitude are plotted on the upper panel of Fig. 9. In general, eddy generation rate is nearly uniform in this latitudinal band, with a slightly enhancement in the southern and northern boundaries. There is a peak of cyclonic eddy generation near 141 o E. A detailed discussion of eddy generation mechanisms will be presented in Sect. 5. The distribution of eddy termination is shown in the lower panel of Fig. 9. The meridional distribution is nearly uniform, which is consistent with the facts that the meridional distribution of eddy generation rate is nearly uniform and these eddies move mostly in the westward direction and eventually die within the same latitudinal band. For eddies generated close to the western boundary, they dissipate their energy and western boundary thus works as a graveyard for these eddies. As a result, the number of eddy termination has a maximum near the western boundary (near the Kuroshio), as shown in the lower-right panel of Fig. 9. Fig. 10 shows seasonal variations in eddy generation and termination. There is a peak in early spring (February and March) and a trough in summer (July) for eddy generation. Eddy termination peaks are delayed by one or two months. There is no significant difference between cyclonic and anticyclonic eddies in terms of seasonal variation; however, there are slightly more cyclonic eddies generated than anticyclonic eddies. There is a minimum in eddy generation around the year of with smaller seasonal variation than other years, and a similar pattern can be seen for the eddy 11

12 230 termination Eddy Evolution An eddy can be characterized by its parameters such as: eddy radius, vorticity, kinetic energy and deformation rate. The eddy kinetic energy is defined as the averaged kinetic energy within an eddy area (defined from the eddy center to its boundary). The eddy deformation rate is defined as, where and are shear deformation rate and stretching deformation rate [Carton, 2001; Hwang et al., 2004]. These parameters evolve with time during the lifetime of each eddy. To describe the mean evolution of eddies, we consider eddies longer than 20 weeks, and the total number of such eddies are: 941 cyclonic eddies and 859 anticyclonic eddies. We introduce an eddy age normalized by its lifespan. For each eddy, the time evolution of four basic parameters discussed above can be represented by the time evolution of the non-dimensionized variable based on the corresponding maximum in its lifespan of each eddy. Averaging over all eddies with lifespan longer than 20 weeks, we obtained the normalized temporal evolution for these four parameters, as shown in Fig. 11. It is readily seen that eddy size, vorticity magnitude and kinetic energy increase in its first 1/5 of life cycle (youth) and then stay stable for next 3/5 of its life cycle (adult). In the last 1/5 of the mean life cycle (aged), these parameters decrease sharply. The deformation rate shows the opposite trend, in its first 1/6 of life cycle (youth), the rate decreases and then stays roughly constant for next 2/3 of the life cycle and finally increases sharply before eddies die eventually. The life cycle of vorticity has a similar feature for both the cyclonic and 12

13 anticyclonic eddies. However, the magnitude of the mean vorticity for anticyclonic eddies is larger than that of cyclonic eddies. In addition, the magnitude of the mean vorticity of the anticyclonic eddies is larger than that of cyclonic eddies, and this is consistent with the information presented in Fig Eddy Movement Fig. 12 plots trajectories of eddies with lifetime longer than 50 weeks. All these eddies move westward. Some eddies generated near Hawaii islands can move all the way to the area near the Kuroshio. Thus, it is more meaningful to combine the zone of subtropical counter-current and the lee side of Hawaii Islands as a united area in this study as we stated in Introduction. The westward velocity of eddies varies with the latitude. The left panel of Fig. 13 shows that the westward velocity averaged within a band of 1 decreases with the latitude, which is due to the β effect and self advection [McWilliams and Flierl, 1979]. The right panel of Fig. 13 shows the northward velocity averaged a band of 1 varies with latitude, it is equatorward north of 21 N and poleward south of 21 N for both cyclonic and anticyclonic eddies with the speed in 1 cm/s. As the eddy movement is affected by both the mean flow and the β effect, the meridional eddy moving velocity could be affected by the regional mean circulation, which results in a deflection in the meridional direction. The combination of the equatorward movement in the northern half of the band and the poleward movement in the southern half of the band may induce high concentration of eddies of mature stage when eddies reach their largest sizes during their life spans (Fig. 11) in the middle latitude of this zonal band, which results in the large eddy size along the middle latitude as shown in Fig.6. 13

14 Eddy Interaction with the Kuroshio As discussed above, eddies move westward and some long-lived eddies can be traced back to the lee size of Hawaii Islands. When the westward propagating eddies encounter Kuroshio, what will happen? Using a numerical model and SSHA data, Zhai et al. [2010] postulated that the western boundary area is a graveyard for westward propagating eddies. On the other hand, Numerical solution by Sheu et al. [2010] suggests that some eddies can penetrate the Kuroshio and enter the South China Sea. In the following subsection, we will use the eddy dataset to explore this issue in detail. Two cases (one cyclonic eddy and one anticyclonic eddy) are selected to show how an eddy interacts with the Kuroshio. Figure 14 shows a cyclonic eddy moves northwestward and then towards the Luzon Strait. The eddy stays southeast of Taiwan for about three weeks. Finally, it merges into the Kuroshio near southeast of Taiwan. Figure 15 displays the movement of an anticyclonic eddy first seen southeast of Taiwan. This eddy eventually moves across the Luzon Strait. To have a more accurate accounting for the eddy interaction with the Kuroshio, we choose a box (120 E ~126 E and 18 N ~23 N) shown in Fig. 16, and the number of eddies moving into or out of the box is listed along each boundary. Note that some eddies might cross boundaries for a few of times. Thus, if an eddy is born outside the box and dies within the box, we record the first time when it enters the box; however, if it dies outside the box, we record the last time when it leaves the box. On the other hand, if an eddy is born in the box, we will only record the time when it leaves box finally. In total, 162 cyclonic (146 anticyclonic) eddies enter the box and 105 cyclonic (88 anticyclonic) 14

15 eddies leave the box across the four boundaries. Note that the total numbers of eddies entering and leaving the box are not exactly balanced because some eddies are born/die in the box. In 17 years, 251 cyclonic (265 anticyclonic) eddies are generated in the box and 308 cyclonic (323 anticyclonic) eddies terminate in the box. Therefore, when eddy numbers are balanced, about 74% cyclonic (78% anticyclonic) eddies die in the box. The rate of eddy termination in the box seems to support the idea that the region near the Kuroshio is a graveyard for westward eddies as suggested by Zhai et al. [2010]. However it should be noted that in the 17 years, only about 100 eddies from over nine thousands of eddies can reach the region near the Kuroshio when they are generated in the zonal band and propagate westward. In other words, most of them die on the way towards the western boundary region. So in this sense, the western boundary area is not a graveyard for westward-propagating eddies. Moreover, it can be seen in the next paragraph that many eddies continue to move westward (cross the Kuroshio) or advect downstream (along the Kuroshio). Among eddies crossing four boundaries, 45 cyclonic (28 anticyclonic) eddies leave the box on the northern boundary, advected by the Kuroshio, in contrast to 8 cyclonic (8 anticyclonic) eddies move against the Kuroshio to cross the southern boundary. 49 cyclonic eddies (50 anticyclonic) eddies pass through the Luzon Strait into the South China Sea. 97 cyclonic (93 anticyclonic) eddies cross the eastern boundary into the box, in contrast to 3 cyclonic (2 anticyclonic) eddies leave the box eastward. 23 cyclonic eddies (26 anticyclonic) eddies enter the box through the southern boundary. To test the sensitivity of the selection of the western line of the box, we move the western line of the box backward to 121 E, 32 cyclonic (29 anticyclonic) eddies pass through the Luzon 15

16 Strait, that implies some eddies are generated within the strait. Though Li et al. [2007] and He et al. [2010] argued that eddies did not pass the Luzon Strait from the Western Pacific into the South China Sea, and Sheu et al. [2010] argued that under certain conditions eddies can penetrate the Kuroshio into the South China sea, and the statistical results seems to support the latter one. Figure 17 shows the seasonal variation in the number of eddies passing the Luzon strait and those advected northward by the Kuroshio. It is shown that the number of cyclonic eddies moving across the Kuroshio and passing the strait is minimum in the summer when the Kuroshio is the strongest which is in phase with the summer monsoon. However the trend for anticyclonic eddies is quite different from that of the cyclonic eddies. The northward movement of eddies, which is apparently induced by the Kuroshio, does not show clear seasonal variation. Sheu et al. [2010] suggested that whether an eddy can cross the Kuroshio and pass through the Luzon Strait or advected northward by the Kuroshio depends on both the strength and the relative horizontal potential vorticity profile of the Kuroshio. It is clear that a detailed explanation of the above statistical result requires more observational data Eddy Impact on Thermocline and Halocline With the altimetry data, we can only see the eddy activities at the sea surface. Argo T/S vertical profiles provide much needed information for the subsurface ocean. In total, Argo vertical profiles are found in the studying zonal band from Sep to Dec. 16

17 , most of which were deployed after First, we interpolate recorded temperature and salinity vertical profiles into vertical levels evenly separated from 10 meters to 1000 meters with an interval of 10 meters. Temporal and spatial information of the detected eddies are used as indices to select the vertical profiles falling in eddy areas. Two criteria are used: since the SSHA data are weekly-sampled and the Argo record is daily-recorded, we select all Argo profiles whose recording time are within a period of 3 days before and after the time when an eddy is presented in the SSHA data and whose locations are within 1.2 time the radius from the eddy center. We identify 1640 vertical profiles within anticyclonic eddies and 1656 within cyclonic eddies. The number of profiles within cyclonic and anticyclonic eddies are almost equal, that is amazing. The mean temperature and salinity vertical profiles for cyclonic and anticyclonic eddies from all Argo profiles in the study area are shown in the panels of Fig. 18. The temperature decreases with depth but the salinity has subsurface maximum at approximately 150 meters below the sea surface. These curves are very close to each other with small differences. To demonstrate the eddy impact on the thermocline and haloclines, the profiles of temperature/salinity anomalies in eddy areas with respect to the mean T/S profiles are shown in the lower panels of Fig. 18. The temperature anomaly profiles show that cyclonic (anticyclonic) eddies induce negative (positive) temperature anomaly which reaches maximum at a depth of 150 meters; the impact of eddies can 360 reach the depth of about 1000 meters. The salinity anomalies profiles show a complicated situation because the salinity maximum is located at 150 meters. Within a cyclonic eddy, high salinity water is pulled upward and water becomes saltier, meanwhile the fresher water below the depth of salinity maximum is also pulled upward and lowers 17

18 the salinity, which results in a thicker layer of fresh water. When an anticyclonic eddy is presented, the fresh water is pushed downward and moved the salinity maximum from 150 meters to 200 meters. Temperature (salinity) anomalies in the thermocline (haloclines) discussed above can be carried by westward-propagating eddies, which could affect the heat and salt balance in the ocean [Roemmich and Gilson, 2001] Eddy Generation Mechanisms What mechanisms drive eddy generation? As discussed in the introduction, this band can be separated into two regions regulated by different dynamics. The western region is the subtropical frontal zone associated with a weak eastward counter current. Using T/S vertical profile along one section of 137 E, Qiu and Chen [2010] suggested that eddies generation in the western part of the zonal band is due to the baroclinic instability associated with the front. The eastern region is coincident with the lee side of Hawaii Islands where wind curl is strongly affected by the presence of islands. Using SSHA data, the close correlation between wind curl and eddy generation in this region was discussed by Yoshida et al. [2010]. In order to examine eddy generation mechanisms in this zonal band, we analyze the AVHRR SST data to estimate the correlation between SST front and eddy generation variations. The monthly SST meridional gradient T/ y (averaged for the zonal band) is calculated. The upper panel of Fig. 19 plots the time series of the zonal averaged SST meridional gradient, which shows strong variability in seasonal and 18

19 interannual time scales. When the cross-latitude averaged, we can see clearly that the seasonal variation in the meridional gradient of SST matches the seasonal variation in the number of eddy generation (Fig. 10): a greater magnitude in SST gradient corresponds to a larger number of eddies generated in the early spring; a smaller magnitude in SST gradient corresponds to a less number of eddies generated in summer. The interannual variation in the bottom panel shows that the magnitude of SST gradient was relatively smaller from , and this is consistent with the lower rate of eddy generation shown in Fig. 10. It should be noted that our analysis was carried over the whole band. This further confirms the argument by Qiu and Chen [2010] that baroclinic instability is responsible for the eddy generation. In addition to the baroclinic instability, the vorticity distribution in lee side of Hawaii Island is spatially well correlated with the distribution of wind stress curl: positive vorticity of eddies and positive local wind curls in the northwest of Hawaii Islands, and negative vorticity and wind curl in the southwest of Hawaii Islands (in lee side), by comparing Fig. 20 with Fig. 7. The role of wind curl in the eddy generation in lee side of Hawaii Islands has been extensively discussed in previous literatures, e.g., Calil et al. [2008], Yoshida et al. [2010]. From the distribution of the wind curl in the whole zonal band, we can see there is a persistent patch of positive wind curl on the southern part. The seasonal variation in wind curl agrees very well with that of generation for both cyclonic and anticyclonic eddies. Such agreement implies the wind curl plays a direct or indirect role in eddy generation in the western part of the band. The interannual variation for wind curls is not discussed here because QuikSCAT wind data do not cover the period prior to year

20 Summary Using the observational data: SSHA, SST, QuikSCAT wind, Argo T/S vertical profiles, this paper analyzes cohesive eddy activities in one zonal band in the subtropical North Pacific Ocean with the second largest eddy activities (the largest one is located in the Kuroshio extension region). A geometry-based eddy detection scheme by Nencioli et al. [2010] is applied to the SSHA-derived geostrophic currents to identify and track eddies. An eddy dataset is set up, which includes spatial and temporal information of eddy generation, termination, evolution, and a series of eddy characteristics parameters. Eddy properties are presented through a series of statistical analysis. The eddy location and time data are used to track vertical profiles of eddies from the Argo data, which exposes how eddies impact the thermocline and halocline in the area. The SST gradient (frontal intensity) derived the SST data is in association with the eddy generation number in both seasonal and interannual scales. The wind curl variation in the area shows a good relationship with eddy generation not only in the lee side of Hawaii Islands but also in western part of the band, which implies wind curl might play a role in the eddy generation either directly or indirectly 425 Acknowledgments: YL and YPG appreciate supports from National Basic Research Program of China (2007CB411801) and the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant KZCX1-YW-12-4). CD appreciates the support from the National Aeronautics and Space Administration (grant NNX08AI84G). The work was partially done when YL visited CD at UCLA and working 20

21 with CD in YL and CD appreciate the support from the State Key Laboratory of Satellite Oceanic Environment and Dynamics, Second Institute of Oceanography, SOA, China. YPG thanks Joint Institute for Regional Earth System of UCLA for the host of YPG s visit at UCLA. We thank Dr. Rui Xin Huang from Woods Hole Oceanographic Institute for his careful reading of and comments on the manuscript. 21

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27 Figure captions Figure 1. The spatial distribution of the high-pass (shorter than 90 days and longer than 7 days) EKE (in unit of cm 2 /s 2 ) spatial distribution in the Northern Pacific Ocean, calculated from altimeter SSHA and averaged over the period of 1993~2009. The AVISO data with a resolution of 1/3 x 1/3 degree spatial resolution and 7 day temporal resolution are used. The rectangular area marked by black lines is focus of the present study (15 N~28 N, 115 E-150 W). Figure 2. Upper Panel: time series of EKE in the study area. The solid line is the 7 days sampled data and the dashed line is the result after 52-week smoothing, which shows the interannual variability. Lower panel: seasonal variation of the EKE obtained from the upper panel through monthly averaging. Figure 3. Hovmoeller plots for EKE (left panel) and normalized vorticity (right panel) in a band of 21 N~23 N. Vorticity is normalized by the background planetary vorticity averaged over the band of 21 N~23 N. Figure 4. A snapshot of eddy distribution on April 30, 2008 for eddy sizes larger 50km. Red and blue dots are denoted to centers of anticyclonic and cyclonic eddies, respectively. The flow field is velocity anomalies derived from SSHA data. Figure 5. Upper panel: histogram of eddy number (for each 10-km bin) against eddy size, where the positive (negative) eddy sizes denote cyclonic (anticyclonic) eddies, respectively. Lower panel: the histogram of eddy number against eddy lifetime. Figure 6. Eddy size distribution: cyclonic (upper panel) and anticyclonic (lower panel). 562 The eddy sizes averaged over 1 x1 bins are displayed in the figure. Unit: km. 563 Figure 7 Top panel: the same as Fig. 6, except for the normalized cyclonic eddy vorticity; 27

28 middle panel: the same as upper panel but for anticycloninc eddies; bottom panel: the meridional mean normalized eddy vorticity as a function of the longitude. Figure 8. Histogram of eddy normalized vorticity with a bin width of 0.02 (only eddies with lifetime equal to or longer than 4 weeks are selected). Figure 9. Left panels: number of eddy generation/termination for each 0.5-degree latitude bin (zonally averaged). Right panels: number of eddy generation/termination for each 2- degree longitude bin (meridionally averaged). Figure 10. Upper two panels: seasonal variation of the number of eddy generation/termination. Lower two panels: interannual variation of the number of eddy generation/termination. Figure 11. The time evolution of mean eddy characteristic parameters: radius (upperleft), vorticity (upper-right), kinetic energy (lower-left) and deformation (lower-right). Each eddy s age is normalized by its life span. Each parameter of each eddy is normalized its maximum magnitude of the parameter, and the mean eddy parameters obtained by averaging over eddies with lifespan longer than 20 weeks are plotted in the figure. Dashed and solid lines denote cyclonic and anticyclonic eddies, respectively. Figure 12. The eddy trajectories (for eddies with lifetime 50 weeks); red lines depict trajectories of cyclonic eddies and blue lines for trajectories of anticyclonic eddies; the solid points are the starting positions, and the star points for the ending positions. Figure 13. Left panel: westward speed (cm/s) of eddies; right panel: northward speed (cm/s) of eddies; the solid line for cyclonic eddies and the dashed line for anticyclonic eddies. These curves represent the mean for eddies with lifetime 4 weeks. Figure 14. The time evolution of a westward cyclonic eddy, which is eventually blocked 28

29 by the Kuroshio. Figure 15. The time evolution of an eddy, which eventually passes through the Luzon Strait. Figure 16. Eddy number budget for a square area enclosed the Luzon Strait: left panel for the cyclonic eddies and right panel for anticyclonic eddies. Two western boundaries are selected to test the sensitivity of the calculation: the solid line is located at 120 E and the dashed line at 121 E. Figure 17. Seasonal variation in number of eddies crossing the western boundary (120 E) (left panel) and the northern boundary (23 N) (right panel) leaving the box depicted in Fig. 16. Figure 18. MeanT/S profiles from Argo data within the study area. Upper-left panel: mean temperature; upper-right: mean salinity; lower-left: mean temperature anomaly (deviation from the mean temperature profile); lower-right: mean salinity anomaly. Figure 19. Upper panel: Monthly averaged SST meridional gradient (in unit of ºC/110km, average the band of 115 E 150 W, 15 N 28 N) from AVHRR 1993 to 2009 with 25 km in resolution. Bottom panel: seasonal variation in the meridional SST gradient. Figure 20. Upper panel: mean wind curl (calculated from QuikSCAT wind data) distribution in the zonal band. Lower panel: monthly mean wind curl and number of eddy generated. 29

30 Figure 1. The spatial distribution of the high-pass (shorter than 90 days and longer than 7 days) EKE (in unit of cm 2 /s 2 ) spatial distribution in the Northern Pacific Ocean, calculated from altimeter SSHA and averaged over the period of 1993~2009. The AVISO data with a resolution of 1/3 x 1/3 degree spatial resolution and 7 day temporal resolution are used. The rectangular area marked by black lines is focus of the present study (15 N~28 N, 115 E-150 W). 30

31 Figure 2. Upper Panel: time series of EKE in the study area. The solid line is the 7 days sampled data and the dashed line is the result after 52-week smoothing, which shows the interannual variability. Lower panel: seasonal variation of the EKE obtained from the upper panel through monthly averaging. 31

32 Figure 3. Hovmoeller plots for EKE (left panel) and normalized vorticity (right panel) in a band of 21 N~23 N. Vorticity is normalized by the background planetary vorticity averaged over the band of 21 N~23 N. 32

33 Figure 4. A snapshot of eddy distribution on April 30, 2008 for eddy sizes larger 50km. Red and blue dots are denoted to centers of anticyclonic and cyclonic eddies, respectively. The flow field is velocity anomalies derived from SSHA data. 33

34 Figure5. Upper panel: histogram of eddy number (for each 10-km bin) against eddy size, where the positive (negative) eddy sizes denote cyclonic (anticyclonic) eddies, respectively. Lower panel: the histogram of eddy number against eddy lifetime. 34

35 Figure 6. Eddy size distribution: cyclonic (upper panel) and anticyclonic (lower panel). The eddy sizes averaged over 1 x1 bins are displayed in the figure. Unit: km. 35

36 Figure 7. Top panel: the same as Fig. 6, except for the normalized cyclonic eddy vorticity; middle panel: the same as upper panel but for anticycloninc eddies; bottom panel: the meridional mean normalized eddy vorticity as a function of the longitude. 36

37 Figure 8. Histogram of eddy normalized vorticity with a bin width of 0.02 (only eddies with lifetime equal to or longer than 4 weeks are selected). 37

38 Figure 9. Left panels: number of eddy generation/termination for each 0.5-degree latitude bin (zonally averaged). Right panels: number of eddy generation/termination for each 2-degree longitude bin (meridionally averaged). 38

39 Figure 10. Upper two panels: seasonal variation of the number of eddy generation/termination. Lower two panels: interannual variation of the number of eddy generation/termination. 39

40 Figure 11 The time evolution of mean eddy characteristic parameters: radius (upper-left), vorticity (upper-right), kinetic energy (lower-left) and deformation (lower-right). Each eddy s age is normalized by its life span. Each parameter of each eddy is normalized its maximum magnitude of the parameter, and the mean eddy parameters obtained by averaging over eddies with lifespan longer than 20 weeks are plotted in the figure. Dashed and solid lines denote cyclonic and anticyclonic eddies, respectively. 40

41 Figure 12. The eddy trajectories (for eddies with lifetime 50 weeks); red lines depict trajectories of cyclonic eddies and blue lines for trajectories of anticyclonic eddies; the solid points are the starting positions, and the star points for the ending positions. 41

42 Figure 13. Left panel: westward speed (cm/s) of eddies; right panel: northward speed (cm/s) of eddies; the solid line for cyclonic eddies and the dashed line for anticyclonic eddies. These curves represent the mean for eddies with lifetime 4 weeks. 42

43 Figure 14. The time evolution of a westward cyclonic eddy, which is eventually blocked by the Kuroshio. 43

44 Figure 15. The time evolution of an eddy, which eventually passes through the Luzon Strait. 44

45 Figure 16. Eddy number budget for a square area enclosed the Luzon Strait: left panel for the cyclonic eddies and right panel for anticyclonic eddies. Two western boundaries are selected to test the sensitivity of the calculation: the solid line is located at 120 E and the dashed line at 121 E. 45

46 Figure 17. Seasonal variation in number of eddies crossing the western boundary (120 E) (left panel) and the northern boundary (23 N) (right panel) leaving the box depicted in Fig

47 Figure 18. MeanT/S profiles from Argo data within the study area. Upper-left panel: mean temperature; upper-right: mean salinity; lower-left: mean temperature anomaly (deviation from the mean temperature profile); lower-right: mean salinity anomaly. 47

48 Figure 19. Upper panel: Monthly averaged SST meridional gradient (in unit of ºC/110km), average the band of 115 E 150 W, 15 N 28 N) from AVHRR 1993 to 2009 with 25 km in resolution. Bottom panel: seasonal variation in the meridional SST gradient.

49 Figure 20. Upper panel: mean wind curl (calculated from QuikSCAT wind data) distribution in the zonal band. Lower panel: monthly mean wind curl and number of eddy generated.